Linear predictive coding (LPC) is one of the more important tools used in the processing of voice information. LPC is a mathematical procedure for estimating a filter function equivalent to the vocal tract. The estimate of the vocal tract resonance may be used to subtract vocal tract resonances from speech leaving an estimate of the excitation. The vocal tract function is estimated by removing correlation between a number of adjacent samples of the speech waveform; assuming that the waveform may be modeled as exponentially decaying sinusoids. The model for decaying sinusoids may be derived by inverting a correlation matrix (an all-pole lattice digital filter) to provide an all-zero lattice digital filter. The LPC correlation, excitation, and amplitude information are each individually quantized and transmitted typically at between 1200 and 4800 bits per second depending on desired speech fidelity, system complexity, and system throughput constraints.
The bandwidth of the LPC digital voice system is set by the number of bits used to describe each measured parameter and the frequency with which this snapshot of the articulators is updated. Predicter coefficients are usually transformed to reflection coefficients before quantization, because reflection coefficients have the nice property of being bounded between the natural limits of +1 and -1. Additionally, the first few reflection coefficients have the most predominant effect on the spectrum and thus can be quantized more finely than higher numbered reflection coefficients. For example, the first reflection coefficient is quantized with six bits while the last reflection coefficient may be quantized with only three bits.
While LPC analysis is computationally quite lengthy, it is mathematically straight-forward. The partial correlation analyzer of the present invention generates a new estimate of each reflection coefficient for each new speech sample.
Lattice structured approaches to LPC provide not only reflection coefficients which result in stable synthesis filters, due to their boundedness, but also provides the residual in a computational procedure which is elegantly simple. The partial correlation procedure for the lattice inverse filter consists of keeping a smooth estimate of the partial correlation between forward and backward transverse waves in the electrical analog vocal tract. These partial correlations relate directly to the reflection coefficients at hypothetical boundaries of a sectioned vocal tract. While it is possible to use general purpose processor approaches to the partial correlation procedure, even with a high performance arithmetic logic unit which could perform fast multiplies, adds, divides, subtracts, shifts, etc., and with very dense memory, power dissipation rapidly becomes prohibitive. Interconnects require a great deal of power consumption to charge and discharge the interconnect capacitance at the system clock rate. Thus a great deal of power is consumed.